MOTION PLANNING OF SWARM ROBOTS USING POTENTIAL-BASED GENETIC ALGORITHM

被引：0

作者：

Lin, Chien-Chou ^{[1
]}

Chen, Kun-Cheng ^{[1
]}

Hsiao, Po-Yuan ^{[2
]}

Chuang, Wei-Ju ^{[1
]}

机构：

[1] Natl Yunlin Univ Sci & Technol, Dept Comp Sci & Informat Engn, 123,Sect 3,Univ Rd, Touliu, Yunlin 64002, Taiwan

[2] Shu Te Univ, Dept Comp Sci & Informat Engn, Kaohsiung 82445, Taiwan

来源：

INTERNATIONAL JOURNAL OF INNOVATIVE COMPUTING INFORMATION AND CONTROL | 2013年 / 9卷 / 01期

关键词：

Swarm robotics; Formation control; Voronoi diagram; Artificial potential field; Genetic algorithm;

D O I：

暂无

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

A potential-based genetic algorithm is proposed for the motion planning of robot swarms. The proposed algorithm consists of a global path planner and a motion planner. The global path planning algorithm plans a trajectory, which the robot swarm should follow, within a Voronoi diagram of the free space. The motion planning algorithm is a genetic algorithm based on artificial potential models. The potential functions are used to keep robots away from obstacles and to keep the robot swarm within a certain distance from each other. Since the proposed approach is a hierarchical algorithm which plans the global path and local motion individually, the robot swarm moves toward the goal by sequentially traversing a sequence of positions along the Voronoi diagram. Therefore, the robot swarm can avoid becoming trapped in local minima.

引用

页码：305 / 318

页数：14

共 50 条

[31] Path Planning of Mobile Robots Based on A* Algorithm and Artificial Potential Field Algorithm
Wang H.
Hao C.
Zhang P.
Zhang M.
Yin P.
Zhang Y.
Zhongguo Jixie Gongcheng/China Mechanical Engineering, 2019, 30 (20): : 2489 - 2496
[32] A Distributed Genetic Algorithm for Swarm Robots Obstacle Avoidance
Rezk, Nesma M.
Alkabani, Yousra
Bedor, Hassan
Hammad, Sherif
2014 9TH INTERNATIONAL CONFERENCE ON COMPUTER ENGINEERING & SYSTEMS (ICCES), 2014, : 170 - 174
[33] Path Planning for Mobile Robots Using Genetic Algorithm and Probabilistic Roadmap
Santiago, Robert Martin C.
Louise De Ocampo, Anton
Ubando, Aristotle T.
Bandala, Argel A.
Dadios, Elmer P.
2017 IEEE 9TH INTERNATIONAL CONFERENCE ON HUMANOID, NANOTECHNOLOGY, INFORMATION TECHNOLOGY, COMMUNICATION AND CONTROL, ENVIRONMENT AND MANAGEMENT (IEEE HNICEM), 2017,
[34] AUV swarm path planning based on elite family genetic algorithm
Feng H.
Hu Q.
Zhao Z.
Xi Tong Gong Cheng Yu Dian Zi Ji Shu/Systems Engineering and Electronics, 2022, 44 (07): : 2251 - 2262
[35] Method of path planning for home security robots based on genetic algorithm
Institute of Robot and Information Automatic System, Nankai University, Tianjin 300071, China
Gaojishu Tongxin, 2007, 9 (924-928): : 924 - 928
[36] Learning Potential-based Policies from Constrained Motion
Howard, Matthew
Klanke, Stefan
Gienger, Michael
Goerick, Christian
Vijayakumar, Sethu
2008 8TH IEEE-RAS INTERNATIONAL CONFERENCE ON HUMANOID ROBOTS (HUMANOIDS 2008), 2008, : 361 - +
[37] PATH PLANNING OF FRUIT AND VEGETABLE PICKING ROBOTS BASED ON IMPROVED A* ALGORITHM AND PARTICLE SWARM OPTIMIZATION ALGORITHM
Li, Chen
INMATEH-AGRICULTURAL ENGINEERING, 2023, 71 (03): : 470 - 482
[38] Motion planning of a nonholonomic multibody system using genetic algorithm
Ge, XS
Chen, LQ
Liu, YZ
INTERNATIONAL JOURNAL OF NONLINEAR SCIENCES AND NUMERICAL SIMULATION, 2005, 6 (02) : 113 - 120
[39] Motion Planning for Car-like Robots Using Hierarchical Genetic Algorithms
Achour, N.
Lakhdari, A.
Ferguene, F.
WORLD CONGRESS ON ENGINEERING - WCE 2013, VOL II, 2013, : 787 - 791
[40] The Motion Planning Based Genetic Algorithm For Wheeled Mobile Manipulator
Zhang Shuosheng
Liu Na
MATERIAL SCIENCE AND ENGINEERING TECHNOLOGY, 2012, 462 : 141 - 146

← 1 2 3 4 5 →